Intuitive strategies to deal with messy data, weak models, and leaky machine-learning pipelines
About This Video
Machine learning is all the rage, and you have been tasked with creating models for your business. What looked simple on the surface quickly becomes a nightmare of messy data and non-performing models. What do you do?
Hands-On Problem Solving for Machine Learning is packed with intuitive explanations of how machine learning works so that you can fix your models when they break. It presents a wide array of practical solutions for your machine learning pipeline, whether you are working with images, text, or numbers. You'll get a real feel for how to tackle challenges posed during regression and classification tasks.
If you want to move past calling simple machine learning libraries, and start solving machine learning problems with real-world messy data, this course is for you!
All the code and supporting files for this course are available on GitHub at - https://github.com/PacktPublishing/Machine-Learning-Problems-Solved-V-
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